Robust adaptive control of the Stewart-Gough robot in the task space

Yime, Eugenio; Saltarén, Roque; Diaz, James

doi:10.1109/acc.2010.5530463

Cited by 12 publications

(6 citation statements)

References 21 publications

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“…The task space equations of motion were developed to control the Stewart platform using combined robust and adaptive controller. The developed equations were obtained using the virtual work approach, [22]. A control scheme combining the dynamics disturbance force forward feed with μ synthesis was suggested in [23].…”

Section: Control Methodologiesmentioning

confidence: 99%

Advanced Control Methodologies in Parallel Robotic Systems

Buzurović¹

2012

Adv Robot Autom

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Section: Control Methodologiesmentioning

confidence: 99%

Advanced Control Methodologies in Parallel Robotic Systems

Buzurović¹

2012

Adv Robot Autom

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“…In recent years, robust control method has been widely employed in dealing with nonlinear control with uncertainties and disturbances [25]. Yime et al [26] proposed a robust adaptive control for the Stewart Gough platform, and the performance of the control law was evaluated by using a sinusoidal path for position and orientation of the upper platform. Zhu et al [27] presented an adaptive robust posture controller for a parallel manipulator driven by pneumatic muscles with a redundant degree of freedom, which can be utilized to deal with parametric uncertainties and uncertain nonlinearities in the dynamics.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Modeling and Adaptive Robust Synchronous Control of Parallel Robotic Manipulator for Industrial Application

et al. 2020

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Control of parallel manipulators is very hard due to their complex dynamic formulations. If part of the complexity is resulting from uncertainties, an effective manner for coping with these problems is adaptive robust control. In this paper, we proposed three types of adaptive robust synchronous controllers to solve the trajectory tracking problem for a redundantly actuated parallel manipulator. The inverse kinematic of the parallel manipulator was firstly developed, and the dynamic formulation was further derived by mean of the principle of virtual work. Furthermore, linear parameterization regression matrix was determined by virtue of command function “equationsToMatrix” in MATLAB. Secondly, the three adaptive robust synchronous controllers (i.e., sliding mode control, high gain control, and high frequency control) are developed, by incorporating the camera sensor technique into adaptive robust synchronous control architecture. The stability of the proposed controllers was proved by utilizing Lyapunov theory. A sequence of simulation tests were implemented to prove the performance of the controllers presented in this paper. The three proposed controllers can theoretically guarantee the errors including trajectory tracking errors, synchronization errors, and cross-coupling errors asymptotically converge to zero for a given trajectory, and the estimated unknown parameters can also approximately converge to their actual values in the presence of unmodeled dynamics and external uncertainties. Moreover, all the simulation comparative results were presented to illustrate that the adaptive robust synchronous high-frequency controller possess a much superior comprehensive performance than two other controllers.

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“…In [14], the authors proposed a hybrid method based on Sliding Mode and Neural Networks, and a robust adaptive controller for a 6-DOF robot has been implemented without requiring inverse dynamic model. In [15], a robust adaptive controller has been designed according to task space dynamic equations. At last, a Stewart Platform was built in Simulink environment of MatLab software.…”

Section: Introductionmentioning

confidence: 99%

Research on Foot Trajectory Tracking of Parallel Wheel-legged Robot based on Dynamic Model Predictive Control

Liu

Wang²,

Chen

et al. 2020

Preprint

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In this paper, the foot trajectory tracking control for parallel structure of the sixwheel-legged robot is investigated. The accuracy of trajectory tracking and dynamic responsewith heavy load are the main challenges of parallel mechanism. To guarantee the tracking performance and improve dynamic response frequency to posture input, a method based on dynamic model predictive control is proposed under the establishment of dynamic model of single leg. Newton-Eulerian equation is derived and converted into a discrete state space expression for velocity loop control, appropriate parameters including prediction time domain, control time domain and proportional gain are determined by co-simulation. Desired sinusoidal trajectories with different frequencies are tracked with satisfactory performance in terms of accuracy and response frequency. Finally, comparative experimental results using BIT-NAZA robot derived from the proposed control strategy indicate that the delay error and amplitude error are better than PI controller under the same conditions. This research can provide theoretical and engineering guidance for accurate planning of intelligent robot, and facilitate the control performance of wheel-legged robot in practical system.

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Robust adaptive control of the Stewart-Gough robot in the task space

Cited by 12 publications

References 21 publications

Advanced Control Methodologies in Parallel Robotic Systems

Advanced Control Methodologies in Parallel Robotic Systems

Dynamic Modeling and Adaptive Robust Synchronous Control of Parallel Robotic Manipulator for Industrial Application

Research on Foot Trajectory Tracking of Parallel Wheel-legged Robot based on Dynamic Model Predictive Control

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